Method for tracking items using a fund processing device

ABSTRACT

Tools for forecasting financial instrument transfers are provided. The tools may include a funds processing system. The funds processing system may be established at a client location. The funds processing system may receive a plurality of items. The items may include one or more financial instruments. The items may include one or more attachments. The items may be processed using the funds processing system. Data corresponding to the items may be transmitted to a financial institution. The data may be used to compute a forecast. The forecast may be based at least on part on data received via the funds processing system. Data analytical models may forecast future requirements. The requirements may be pickup requirements. The pickup requirements may be financial instrument pickup requirements. The forecast may be a time forecast. The time may be an estimated arrival time. The estimated arrival time may be at the financial institution.

BACKGROUND

Businesses and other entities (individually or collectively, “entity” or“entities”) typically require a steady supply of cash and/or otherfinancial instruments to facilitate daily operations. Additionally, anentity may handle, process and/or accumulate a significant amount ofcash and/or other financial instruments on a daily basis.

There is often a preference for such entities to keep sufficient fundsor cash on hand in order to adequately supply the entity for dailypurchasing needs, as well as to provide sufficient change, often in theform of smaller denominations, to one or more customers of the entity.

Entities may receive a volume of cash and/or other financial instrumentsthat exceeds their daily needs. Therefore, there may be a need totransfer cash at numerous times during the day. This may be due in partto a reluctance to keep large sums of cash on hand. The reluctance maybe due to liability and security concerns, a desire to maintain adequatecash flow in an account, or due to a lack of sufficient and adequatestorage space for the cash. Therefore, an entity may desire to schedulemultiple funds transfers, on a daily basis, from the entity to afinancial institution.

Additionally, an entity may desire to exchange larger denominations ofcash for smaller denominations in order to more readily provide changeto customers.

Such entities may temporarily store a portion of their deposits in avault until a transfer service, such as a cash transfer service or anarmored car service, arrives to pick up and transfer the funds toanother location. Once the deposits are moved offsite by the transferservice, an entity is typically unable to track the movement of suchdeposits until, at some later point in time, the deposits clear with thefinancial institution. Moreover, the financial institution may remainunaware of certain deposits that are expected to arrive at, and/or areen-route to, the financial institution.

Therefore, because entities are typically unable to track the movementof their funds, they often remain unaware of the status and progressionof a deposit. It would be desirable, therefore, to provide increasedtracking for the progression and movement of deposits at various points,both in terms of transit time and processing progression.

Further, financial institutions often receive only one update regardingtransfers and deposits originating from an entity. The update istypically received at the close of business. This prevents the financialinstitution from analyzing client needs in real-time and respondingappropriately.

It would be desirable, therefore, to provide for increased monitoringand reporting of entities' fund transfers. It would be further desirableto increase the frequency of such reporting in order to allow for a moreimmediate response to client needs, as well as increased processingefficiency, both by the financial institution and the transfer service.It would be yet further desirable to provide tools for an entity tomonitor the status of fund transfers, and to provide an update on theprogression of the fund transfers.

Therefore, systems and methods for forecasting and reporting funds usageand transfer are provided.

SUMMARY OF THE INVENTION

Apparatus, methods, code and encoded media (individually orcollectively, “the tool” or “the tools”) for forecasting financialinstrument transfers in a complex machine information environment areprovided. The complex machine information environment may beadministered by a financial institution.

The tools may include a funds processing system. The funds processingsystem may be established at a client location. The funds processingsystem may receive a plurality of items at the client location. Theitems may include one or more financial instruments. The items mayinclude one or more attachments. The tools may receive trackinginformation. The tracking information may correspond to one or more ofthe items.

The tools may process one or more of the items. The items may beprocessed using the funds processing system. The tools may transmit datacorresponding to the one or more items. The data may be transmitted to afinancial institution. The data may be transmitted via the fundsprocessing system.

The tools may compute a data analytical model. The data analytical modelmay be used to forecast a result. The forecast may be based at least onpart on data received via the funds processing system.

The data analytical model may forecast a future requirement. Therequirement may be a pickup requirement. The pickup requirement may be afinancial instrument pickup requirement.

The data analytical model may forecast a time. The time may be anestimated time. The estimated time may be an estimated arrival time. Thetime may be an arrival time of the items at the financial institution.

BRIEF DESCRIPTION OF THE DRAWINGS

The objects and advantages of the invention will be apparent uponconsideration of the following detailed description, taken inconjunction with the accompanying drawings, in which like referencecharacters refer to like parts throughout, and in which:

FIG. 1 shows illustrative information in accordance with the principlesof the invention;

FIG. 2 shows illustrative apparatus in accordance with the principles ofthe invention;

FIG. 3 shows other illustrative apparatus in accordance with theprinciples of the invention;

FIG. 4 shows still other illustrative apparatus in accordance with theprinciples of the invention;

FIG. 5 shows illustrative steps of a process in accordance with theprinciples of the invention;

FIG. 6 shows other illustrative steps of another process in accordancewith the principles of the invention;

FIG. 7 shows still other illustrative steps of another process inaccordance with the principles of the invention;

FIG. 8 shows yet other illustrative steps of another process inaccordance with the principles of the invention;

FIG. 9 shows yet other illustrative steps of another process inaccordance with the principles of the invention;

FIG. 10 shows illustrative steps of yet another process in accordancewith the principles of the invention;

FIG. 11 shows illustrative steps of yet another process in accordancewith the principles of the invention.

DETAILED DESCRIPTION OF THE INVENTION

Apparatus, methods, code and encoded media (individually orcollectively, “the tool” or “the tools”) for increasing financial datatracking efficiency in a complex machine information environment areprovided. The environment may be administered by an institution. Theinstitution may be a financial institution.

The tools may include a funds processing system (“FPS”). The FPS may bea funds processing device (“FPD”). The FPS may be any suitable apparatusfor processing information. The FPS may be any suitable apparatus forreceiving one or more items. The FPS may be a kiosk, a terminal, anautomated teller machine (“ATM”), a self-service device (“SSD”), a cashhandling device or any suitable apparatus for receiving information oritems.

The FPS may be a stand-alone FPS. The FPS may be located at a remotelocation. The FPS may be established at the remote location. The remotelocation may be a client location. The FPS may be part of a network ofmultiple FPSs. The FPS network may be operated or maintained by afinancial institution. The FPS may be serviced or maintained by thefinancial institution. The FPS or FPS network may be serviced ormaintained by a third party.

The FPS may include an acceptor. The acceptor may be configured toaccept one or more items. The acceptor may be configured to receive oneor more items. The items may be collected by the FPS. The acceptor maybe a feeder. The feeder may feed the items to one or more additional FPScomponents.

The FPS may receive an item. The item may be one or more items. The FPSmay receive a plurality of items. The item may be received at a clientlocation.

The item may be any tangible item. The item may be an item of monetaryvalue. The item may be a bank note, U.S. Treasury note, check, cash,promissory note, warrant, bond, payment slip, stock certificate, paymentreceipt, T-bill, negotiable instrument or any other suitable financialinstrument (individually or collectively, “the financial instrument” or“the financial instruments”). The item may be any item with noassociated monetary value. The item may be an attachment. The attachmentmay be a record, image cash letter, contract, payment stub, photograph,table of contents, account identifier, account destination list, file,memo, voucher, ticket, receipt or any other suitable document(individually or collectively, “the attachment” or “the attachments”).

The acceptor may be configured to retract one or more of the items. Theretracted items may be items inserted by a client. The retraction may beperformed by an automated retraction apparatus.

The FPS may include a sensor. The sensor may be a scanner, a camera, ascale, a measuring device, a bill counter, an optical device or anysuitable sensor. The sensor may examine the items. The camera mayphotograph the items. The photograph may be stored in computer-readablememory. The photograph may be transmitted to an off-site server ordatabase.

The sensor may weigh one or more of the items. Each item in a group ofitems may be weighed individually. Each item may be weighed as part ofan associated grouping. For example, all items of monetary value may beweighed together. Weight information may be used for any suitablepurpose, such as shipping or transport calculations, validity orcounterfeiting analysis, value of notes, or number of notes.

The sensor may extract information. The information may be any suitableinformation that may be extracted from one or more items. Exemplaryinformation may include number of items, type of items, denomination ofitems, value of items, weight of items or any other information that maybe included on or within the items. The information may also bedetermined by type of item, such as number of checks or value of cash.

The information may include condition of items, validity of items or anyuncertainty about the item. The uncertainty may include an errormessage, a determination that an item is counterfeit, or a flagging ofan item for further review. Determination that an item is counterfeitmay be accomplished using any suitable means, such as a marking,chemical testing, fiber testing, optical scanning, or weightmeasurements. The necessary tools and components for counterfeitdetermination may be located inside of the FPS.

The sensor may scan each item. The sensor may detect defects,denomination, counterfeit, origination of currency, and type of item.For example, the sensor may determine that the item is a $20denomination bill. In a further example, the sensor may determine thatthe item is a check. In yet a further example, the sensor may determinethat the item is counterfeit, or possibly counterfeit.

The sensor may collect data. The data may be data about the item. Thedata may be data corresponding to the item. The data may be processed.The data may be used in substantially real-time for analytic models. Thedata may be used at later time for analytics.

The FPS may include a feeder network for transferring an item from theacceptor to the sensor. The feeder network may include rollers, belts,tracks, picks, motors, magnets, suction pads or any other suitablecomponents.

The FPS may include one or more storage cartridges. The storagecartridge may receive one or more items from the sensor. The storagecartridge may be configured to store one or more of the items. Thesensor may be located along a feeder network connecting the acceptor tothe storage cartridge. The storage cartridge may receive one or moreitems from the acceptor. The feeder network may transfer the item fromthe acceptor to the storage cartridge.

The acceptor may receive an item. The item may be transferred from theacceptor to the sensor. The item may be transferred via the feedernetwork. The feeder network may transfer the item from the sensor to thestorage cartridge.

The storage cartridge may include a sensor. The storage cartridge mayinclude a floor. The floor may support one or more tangible items storedin the storage cartridge. The floor of the storage cartridge may includethe sensor. The floor may be supported by one or more struts. The strutsmay include the sensor.

The item may be stored in the storage cartridge. The sensor may beremovable from the storage cartridge. For example, the sensor may sit ontop of the storage cartridge floor. The sensor may be detachable fromthe storage cartridge floor.

The storage cartridge may receive one or more items collected by theacceptor. The storage cartridge may be removable from the FPS. Thestorage cartridge may be configured to store one or more of thecollected items received by the acceptor. The items may be stored in thestorage cartridge until the FPS is serviced. For example, an item may becollected by the acceptor. The acceptor may transfer the item to thestorage cartridge via the feeder network. The item may be stored in thestorage cartridge until a pickup.

The pickup may be a transfer, transport or supply. The pickup may be apickup of the items inside the storage cartridge. The pickup may be apickup of the storage cartridge. The pickup may transport the items in astorage cartridge. The store cartridge may be transported to a facility.

The FPS may include a plurality of storage cartridges. Each storagecartridge may be designated to receive one or more items. Each storagecartridge may be filled in sequence until the cartridge is at capacity.For example, once the first storage cartridge is at capacity, all itemsmay be stored in a second storage cartridge.

Each storage cartridge may be designated to receive one or morespecified categories of items. For example, all attachments may bestored in a first cartridge. In another example, all items of monetaryvalue may be stored in a second cartridge.

The FPS may be configured to transfer each unique denomination to aseparate storage cartridge. The FPS may be configured to transfer eachtype of document to a separate storage cartridge. For example, a checkmay be stored in a first storage cartridge. In another example, areceipt may be stored in a second storage cartridge.

The FPS may be configured to flag one or more items. The flag may be alabel, flag, tag, highlight or any other suitable identifier. Theflagged items may be stored in a storage cartridge. One or more storagecartridges may be configured to only receive flagged items.

The FPS may transmit data corresponding to the flagged item. The datamay include a photograph, type of item or any suitable indicator. Thedata may be transmitted to the financial institution.

The FPS may identify one or more flagged items. The flagged items may beidentified to a financial institution. The FPS may identify thepercentage of flagged items, the quantity of flagged items, thepotential value of flagged items, the motivation for flagging theflagged items or any other suitable identifier.

The FPS may flag counterfeit items. The FPS may flag items that may bepotentially counterfeit. The FPS may flag items to indicate a requestfor further review. The further review may be performed at the financialinstitution. The review may include more detailed processing andanalysis. The FPS may flag items that do not scan properly. The FPS mayflag items from which data cannot be properly extracted.

The sensor may be configured to detect unrecognizable items. The FPS mayflag the items and transfer the unrecognizable items to a storagecartridge. The storage cartridge may be designated to receive flaggeditems. The FPS may store data corresponding to the unrecognizable itemsin computer-readable memory. At a point in time, the FPS may transmitthe data corresponding to the unrecognizable items to the financialinstitution. The point in time may be a time in the immediate or nearimmediate future. The point in time may be any future point in time.

The flagged items may be transferred. A pickup may be scheduled totransfer the flagged items.

The tools may include a processor. The processor may process one or moreitems. The processor may process data associated with one or more items.The processor may communicate with one or more of the acceptor, sensor,storage cartridges, scanner or memory. The processor may be located atthe client location. The processor may be located within the FPS. Theprocessor may be located at a location of the financial institution.

The tools may be configured to transmit data. The data may betransferred using the FPS. The FPS may include a transmitter. The datamay be data corresponding to one or more items. The items may be theitems collected by the acceptor. The data may be any suitable data.

The data may be transmitted to any suitable party. The party may be afinancial institution. The data may be transmitted to a server. The datamay be transmitted to a client server. The client server may transmitdata from one or FPSs to the financial institution. The client servermay transmit data from one or client locations to the financialinstitution.

Some, all or none of the data may be transmitted to a third party. Thethird party may be an independent contractor or vendor. The third partymay be contracted with one or both of the client and financialinstitution. The third party may utilize the data for logisticalpurposes. Based on the data, the third party may transmit data to oneboth of the client and the financial institution. The data may includeestimated costs, arrival time, departure time, travel time or any othersuitable data. For example, based on the weight of the items transmittedto a third party cash transfer service, the third party may determinethe type of vehicle required for pickup. In a further example, the thirdparty may determine a cost estimate for delivery of one or more items.

The tools may include a sorter. The processor may be configured to sortone or more items. The processor may instruct a sorter to sort theitems. The sorter may be a component residing within the FPS. The itemsmay be sorted by item type. For example, the FPS may place a financialinstrument into a first group. In another example, the FPS may place anattachment into a second group.

The items may be sorted by denomination. For example, a $5 bill may beplaced into a first group. In a further example, a $20 bill may beplaced into a second group.

The items may be sorted using any suitable method. For example, theitems may be identified using an optical scanner. The optical scannermay determine similar items based on pre-determined or pre-definedcharacteristics. The optical scanner may transmit the scan to theprocessor. The processor may instruct the sorter to place an item into agroup.

The sorter may be configured to communicate with one or more of thestorage cartridge, acceptor, sensor, processor or modem. Thecommunication may be via the feeder network.

The processor may be further configured to compile a file. The file maybe an image. The image may be an electronic image. The image may be aphotograph. The image may be an image of each item collected or receivedby the FPS.

The file may a data file. The data file may be a CSV file, wordprocessor file, or any other suitable file. The file may be one largefile. The file may be a unique file for each item collected by the FPS.The file may include information extracted from an item. The file may bea folder containing one or more files.

The processor may be configured to compute a sum. The sum may be the sumof the total number of financial instruments collected by the FPS. Thesum may be computed within any suitable time frame. For example, theprocessor may compute the number of financial instruments collected bythe FPS during the present hour, day, week, month or any other suitabletime frame.

The sum may be the sum of the total number of non-financial instrumentitems collected. For example, the sum may be the total number ofattachments collected by the FPS. The sum may be the total number of allitems collected by the FPS. The sum may be the total number of itemscollected for each denomination. The sum may be the total number ofitems collected for each type of item.

The processor may be further configured to calculate a value. The valuemay be a monetary value. The monetary value may be the monetary value ofthe items received by the FPS. The value may be calculated for one ormore items received within a predetermined time frame. The processor maybe configured to determine the denomination of each item.

The financial institution may receive data. The data may be datacollected by the FPS. The data may be data transmitted via the FPS orFPS network. The FPS may transmit the data to the financial institution.The data may be transmitted to the financial institution prior to theremoval of the items from the FPS. The data may be transmittedimmediately upon the collection of data by the FPS. The data mayoriginate from a client. Data may originate from a third party. Thethird party data may be based on data received from the client.

The FPS may transmit the sum of the number of the items. The FPS maytransmit the monetary value of the items. The FPS may transmit thequantity of items for each denomination.

The financial institution may process the data. The financialinstitution may configure the FPS to process the data onsite. The FPSmay contact one or more offsite networks or servers to contribute todata processing. The FPS may process the data entirely onsite.

The financial institution may process the data models. The financialinstitution may compute one or data models. The model may be computedbased on data. The model may be a data structure. The model mayincorporate data from one or more of the client, financial institution,third party or any other suitable data. The data may be the datareceived by the financial institution from a client. The model may be aforecast. The model may be an analytical model. The analytical model mayinclude data analysis. The model may be a relational model. The modelmay be a statistical model.

The relational model may forecast data. The relational model may bebased on the relationship or correlation between two or more variables.The forecast may be a prediction of results.

The model may be used to make one or more predictions. The predictionmay be based on the relationship or correlation between two or more dataelements. The data elements may be variables. For example, based on boththe time of day and the expected travel time to transfer a storagecartridge from the client to a processing center, the model may predictone or more preferred times for a cash replenishment delivery.

Each forecast may be unique to a specific client. The data model may beused to forecast client needs. The data model may be used to forecast aresult, output, consequence, outcome or effect. The data model may beused to forecast client requirements or preferences. The data model maybe used to forecast predicted client usage of additional services oraccounts offered by the financial institution. The data model may beused to forecast preferred or optimal times for interactions between theclient, financial institution and/or third parties. For example, thedata model may predict an outcome based on input of client data,financial institution data and/or data received from a cash handlingservice. In a further example, the data model may determine an optimaldaily cash delivery time for a client using a specified cash handlingservice. In yet a further example, the optimal time may be a timeconvenient for all three parties, such as a time at which the client isable to devote required manpower to receiving and processing the cash.

The data model may be used to forecast receipts. The receipts may beexpected receipts or deliveries for any suitable time frame. Thereceipts may be forecasted based on items received by the FPS.

One or more data models may be used to forecast client cash-flow. Thedata model may forecast client cash-flow at different points in time.The data model may be used to forecast one or more deficiencies. Thedeficiency may be a client deficiency. The forecast may be calculated inreal-time or substantially real-time. The forecast may be a deficiencypredicted to occur in the immediate future, or at some point later intime. The deficiency may be an expected deficiency. The deficiency maybe forecast based on one or more items. The items may be the itemsreceived by the FPS.

The deficiency may be forecast based on collected data. The collecteddata may be used to calculate data models. The data may be historicaldata. The data may be current data.

The data may be received via a live stream or feed. The data maycontinuously update. The updates may occur as a result of the livestream or feed. The update in data may result in one or more updates toforecast models.

It should be noted that preferably all forecasts, predictions,estimates, models or analysis may be updated. The update may be inreal-time. The update may be a batch update at pre-determined intervals.The update may occur continuously based on real-time information. Theupdates may be transmitted to one or more parties in real time, or anysuitable time interval.

The data may incorporate client data. The data may incorporate usagedata, client history, client account history, and client trends.

For example, the data may include client usage of financial instruments.The usage may be a total usage, an average usage, median usage, or anyother statistical variation. The usage may be usage of financialinstrument by type. The usage may be usage of financial instrument bydenomination. The usage may be a calculated quantity. The usage may bedetermined for any suitable interval of time, any period of time, or anyother suitable interval.

The quantity of usage, denominations, or value may be a daily quantity.The daily quantity may be daily client requirements for a financialinstrument. The daily quantity may be the quantity of financialinstruments processed by the client. The quantity may be the quantity ofcash on hand needed by the client. The quantity of cash on hand may bedetermined for each denomination.

The client data may include temporal data. The temporal data may beaverage temporal data. The temporal data may identify one or more pointsin time. The time may be a preferred delivery time. The time may be apreferred pickup time. The delivery may be a delivery of financialinstruments. The time may be a time of peak client consumption of cashon hand.

Temporal, usage, quantity or other suitable forecasts, predictions, orestimates may be determined for any suitably identified segment. Forexample, forecasts of quantity deficiencies may be divided into anysuitable time frame, such as hourly forecasts, or AM and PM forecasts.In another example, forecasts of usage may be divided into forecasts ofusage type (e.g., checks), forecast of quantity of usage (e.g., numberof checks used) or forecast of usage in a time frame (e.g., checksprocessed in the morning).

A preferred delivery time may be identified for each denomination. Apreferred pickup time or delivery time may be determined based onconvenience to the client. The preferred time may identify an averagetime of day when a delivery is favored. The preferred time may identifyan average time of day when a pickup is favored.

Exemplary information for identifying a preferred time may include timeof day when the client requires replenishment of cash on hand, clientusage, day of week, client convenience, client staffing, or any othersuitable information.

The data may incorporate non-client data, such as geographic locationdata, traffic patterns, weather patterns, roads, third party data,seasonal information, or any other suitable data.

The data may incorporate financial institution data. The financialinstitution data may include capacity of processing center, location ofprocessing center, distance to processing center, hours of service,average backlog, and any other suitable data.

The data may incorporate multiple variables such as the preferences ofmultiple parties, historical results, cost containment and any othersuitable variables.

The forecast may be transmitted to the client. The transmission may bein real time. The forecast may be transmitted to any suitable clientdevice. The forecast may be transmitted to the FPS. The FPS may includea display. The display may display the forecast.

It should be noted that any communication between the client, financialinstitution and/or third parties may occur using one or more of aproprietary network, internal network, intranet, third party processingplatform, financial institution interface, messaging device or platform,application, e-mail or any other suitable communications system.

The client may configure one or more automated communicationpreferences. The financial institution may configure one or moreautomated communication preferences. For example, the financialinstitution may transmit automatic updates or queries to the client. Theupdates or queries may be triggered upon the client reaching athreshold. The threshold may be a predetermined threshold. In a furtherexample, the client may configure a threshold amount. The thresholdamount may be any suitable monetary value, such as $10,000. The clientmay request, or the financial institution may provide, an automatedcommunication asking the client if the client would like to request morecash on hand.

The threshold value may be determined based on prior occurrences. Forexample, a query to the client may indicate that, in the majority ofinstances where the client deposited an amount exceeding $500 into theFPS, a delivery of $1 bill denominations has been requested. Therefore,in a further example, the query may ask the client if the client wouldlike to request a delivery of $1 bill denominations.

The forecast may not be transmitted to the client. For example, thefinancial institution may utilize the forecast for internal processingimprovements. In a further example, the financial institution mayutilize the forecast to determine preferred institution processingtimes.

The forecast may analyze trends. The trends may be client trends. Theclient trends may be client usage trends. The client usage trends may beprevious client usage trends. The usage trends may be a client's trendof previous usage of cash on hand. The usage may be total cash on handusage. The usage may be cash on hand determined for each denomination.The usage may be usage within a specified time frame.

The forecast may be calculated based on an evaluation of current usage.The current usage may be a trend. The current usage may be the client'scurrent usage. The current usage may be the client's usage for thecurrent day. The usage may be usage of cash on hand.

The forecast may be calculated using a metric. The forecast may becalculated using an algorithm. The forecast may predict one or morefuture deficiencies. The deficiency may be a client deficiency. Theclient deficiency may be a deficiency for cash on hand. The cash on handdeficiency may be a deficiency for total cash on hand by monetary value.The deficiency may be determined for each denomination. The deficiencymay be a financial institution deficiency. The future deficiency may bea predicted deficiency for the current day, next day, week, or any othersuitable time frame.

The forecast may be used to modify a schedule. The forecast may be usedto suggest a modification to a schedule. The schedule may be a deliveryschedule. The schedule may be the delivery schedule for one or morefinancial instruments. The financial instruments may be delivered by athird party. The third party may be any suitable cash handling ordelivery service. The financial instruments may be delivered by thefinancial institution. The financial instruments may be delivered to theclient.

The forecast may be used to make a recommendation. The recommendationmay include any suitable recommendation. For example, the recommendationmay recommend, based on a prediction, procedures to increase efficiency.

The forecast may be used to recommend a modified schedule. The modifiedschedule may be a modified delivery schedule. The modified schedule maybe a modified pickup schedule. The forecast may be used to recommend aschedule for financial instrument replenishment. The recommendation mayinclude different recommendations for each denomination. The forecastmay be used to recommend an immediate cash transfer.

The forecast may be used to calculate an optimal delivery schedule. Theforecast may be used to predict a preferred delivery schedule. Theforecast may be used to calculate delivery options. The delivery optionsmay include one or more estimates. The estimate may be a time estimate.The time estimate may estimate average time of transit for transfers,average processing time, average time for an account to reflectdeposits, and any other suitable time estimate.

The tool may calculate an estimated arrival time of one or more items.The financial institution may calculate an estimated arrival time of theitems. The arrival may be the arrival of the items at a financialinstitution. The arrival may be the arrival time at a stop orcheckpoint. The financial institution may be a branch, sorting center,processing center, regional processing center, processing facility,sorting facility, contracted third-party facility or any other suitablefacility.

The tool may forecast or predict arrival time. The arrival time may becalculated based on the time of departure of the items from the client.The arrival time may be calculated using any suitable historical orcurrent conditions.

The tool may include a tracking feature. The tool may be linked,connected to, or otherwise in contact with a tracking feature ortracking apparatus. The tool may receive tracking information. Theclient may receive tracking information via the tool. The financialinstitution, or a third party, may receive tracking information via thetool. The tool may include a display. The display may display trackinginformation. The client may receive one or more tracking informationupdates. The updates may be in real-time or substantially real-time. Theclient may customize preferences for updating tracking information.

The client may retrieve tracking information. The tracking informationmay be transmitted to the client. The tracking information may betransmitted to a client device. The tracking information may beretrieved by the client. The tracking information may be available tothe client by accessing a log-in screen. The log-in screen may be a userinterface. The tracking information may be transmitted to the client'semail.

The tracking information may be linked to a proprietary tracking feed.The feed may include information from the financial institution, clientand/or any suitable third parties. The feed may also display forecastinformation, time estimates, item processing information and any othersuitable information.

The tracking information may be calculated using information input byone or more of the client, financial institution and third party.

The tracking information may include a barcode. The barcode may begenerated. The barcode may be unique barcode. The barcode may identify aspecific container. The container may be any suitable container, such asa bag, sack, satchel, item, package, receptacle or storage cartridge.The barcode may be generated by the FPS, client, third-party, deliveryservice, or financial institution. The barcode may be printed. Theprinter may be located within the FPS. The FPS may print a barcode. TheFPS may affix the barcode to a storage container. The storage containermay be removable from the FPS.

The barcode may be scannable. The barcode may be scanned to viewinformation. When scanned, the barcode may retrieve information. Theinformation may include information corresponding to one or more items.The barcode may be linked to the information.

The barcode may be scanned to update information. For example, thebarcode may be affixed to a container. The barcode may be scanned at oneor more points in transit, such as a stop, intermediate or finalprocessing facility, or checkpoint. In response to the scanning, thetool may determine the current location of the container. The tool maytransmit the current location of the container to the client. The toolmay transmit the current location of the container to the financialinstitution. In response to the scanning, the tool may log any suitabledata associated with the container. For example, the tool may log thelocation and time of the barcode scan. The tool may log an identifierassociated with the scanner, such as a scanner ID, log-in, signature, orother suitable identifier.

The tool may update one or more forecasts based on the scan. The updatemay be a recalculation. For example, the tool may update the estimatedtime of arrival of a container at a processing center. In a furtherexample, the tool may update the estimated time that the transferredfunds are expected to clear. The expected time of clearance may be usedto predict fund availability to the client. The FPS may transmit theupdated forecasts to any suitable party using any suitable method.

The barcode may correspond to, cause to retrieve, or be linked to, oneor more data records. The barcode may be linked to data corresponding tothe items in the container. The barcode may be scanned to retrieve alldata corresponding to the items in the container. For example, thebarcode may be scanned upon arrival at the financial institution. Uponscanning the barcode, the financial institution may retrieve informationabout the items. The information may be information corresponding to theinitial processing of the items at the client location. For example, theinformation may include scanned images of the items upon being collectedby the FPS. The information may include any other suitable informationdetermined via the FPS sensor, such as weight, denomination, value,condition code, error, or error percentage.

The tool may include a first FPS and a second FPS. The first FPS andsecond FPS may be operationally identical. The first FPS may be locatedat a client location. The second FPS may be located at a financialinstitution.

Upon receiving the items, the financial institution may insert the itemsinto the second FPS. The second FPS may scan the barcode. The FPS mayinclude a barcode scanner. The barcode scanner may be an internalcomponent of the FPS. The FPS may determine if the items received at thefinancial institution are identical to the items inserted into the firstFPS at the client location. The second FPS may log any variationsbetween the record of the scan at the first FPS and the current scan.The second FPS may determine one or more variations of total number ofrecords, quantity by type, quantity by denomination, total monetaryvalue or any other suitable record.

The historical data may include previous cash transfer data. The datamay correspond to a time. The time may be an amount of time. The timemay be an average time. The time may be a processing time. The time maybe an amount of time to process a document.

Condition data may include current or past traffic conditions, weatherconditions, processing center volume, time of day, current itemlocation, number of non-cash items, number of cash items, number offlagged items or any other suitable condition.

The location may be determined using a tag or locator. The tag may be ageographic location tag.

The financial institution may determine a client error rate. The errorrate may be a percentage. The error rate may be a score. The error ratemay indicate a quantity of client success utilizing the FPS. Forexample, the error rate of Client “Q” may be 1.2%, indicating thatClient Q successfully inputs 98.8% of items into the FPS. In a furtherexample, clients may be assigned a score using any suitable metric. Inyet a further example, a client with an error score less than 1% may begiven a rating of “4” out of 5, with 5 being the highest possible score.In yet a further example, a client with a rating of “4” may be offered adiscount, such as a 5% reduction on deposit processing costs, relativeto those clients with a rating of “3,” or any other suitable promotion.

The financial institution may generate a tiered scoring system. Clientsscoring within a certain tier may be granted certain value-addedservices, such as discounts, offers, premium features or any othersuitable service. Clients meeting and maintaining certain thresholds mayqualify for certain account features. For example, clients achieving andmaintaining a 0% error rate for a certain pre-determined threshold timeperiod may be offered provisional credit. The provisional credit may bea temporary credit. The provisional credit may be transferred topermanent credit upon clearance of the items by the financialinstitution.

The tool may include a tracking device. The tracking device may providetracking information. The tracking device may generate a barcode. Thebarcode may correspond to one or more items. The barcode may correspondto data. The barcode may correspond to one or more containers. Thebarcode may be affixed to, attached to, or otherwise associated with thecontainer. The barcode may correspond to data associated with one ormore items. The barcode may correspond to data associated with one ormore containers.

The tool may generate a barcode. The FPS may generate a barcode. Thetracking system may include a barcode generator. The barcode generatormay reside within the FPS. The tool may print the barcode. The tool maycontain a printer. The printer may reside within the FPS. The printermay be associated with the tracking system.

The barcode may be affixed to one or more items. The barcode may beaffixed to a container or any other suitable object. The barcode may beaffixed to a package. The package may contain one or more items.

The barcode may be scanned. Upon scanning, the barcode may retrievedata. The data may be retrieved by the scanner. The data may beretrieved by any suitable device. The device may not be physically incontact with the scanner.

The barcode may be associated with data. The data may be datacorresponding to one or more items. The data may be any datacorresponding to an item. For example, the barcode may retrieve theweight of the item when it was first received by the FPS. In a furtherexample, the barcode may retrieve a photograph of the item upon theinitial collection of the item by the FPS.

The tool may transmit tracking information. The tracking information maybe transmitted via the FPS. The tracking information may be transmittedto a financial institution. The tracking information may be transmittedto a client. The tracking information may be transmitted to a thirdparty.

The tracking information may include a package identifier. The trackinginformation may include any suitable tracking information. The trackinginformation may include one or more scanning times, item weight, packageweight, estimated time of delivery, estimated time remaining untildelivery, and estimated cost of transport.

The tool may further include a scanner. The scanner may scan thebarcode. The barcode may link to data. The barcode may retrieve data.After the barcode is scanned, the tool may retrieve data. The data maybe associated with the barcode. The data may correspond to an item. Theitem may be an item in a package.

The tool may scan the barcode when one or more items are received. Thebarcode may be scanned immediately upon receiving the one or items inthe FPS. The barcode scan may create a log for the one or more items.The log may be updated.

The barcode scan may generate data. The data may be processed by theFPS. The data may be processed by a client server. The data may beprocessed by a financial institution server. The data may be processedby a third party server.

The data may include any suitable data. The data may include temporaldata. The temporal data may include a time when the item is received bythe FPS. The temporal data may include a time at which the item ispicked up or delivered. The temporal data may include estimates. Theestimate may be an estimated processing time, estimated arrival time,estimated duration of transit or estimated time until funds clear.

The data may include quantity data. The quantity data may include anysuitable number or value. The data may include geographic data. Thegeographic data may identify the location of the item.

The barcode may be scanned at one or more locations. The barcode may bescanned at a first location. The first location may be a clientlocation. The first location may be a financial institution. The firstlocation may be the location of an FPS.

The barcode may be scanned at a second location. The second location maybe any suitable location. The barcode may be scanned using any suitablescanner. The barcode may be scanned at a stop. The stop may be anylocation prior to arrival at a final destination. The stop may be aninterim stop, layover, pickup, drop off, checkpoint, or any othersuitable location for updating a location. The stop may be a stop duringtransfer of the financial instruments.

The barcode scan may be configured to retrieve data. The barcode scanmay retrieve the data when the barcode is scanned at the secondlocation. The data may be associated with the barcode. The data may bedata extracted or determined at the first location.

The tool may be configured to transmit an update. The update may be astatus update. The update may be an updated estimate, prediction orforecast. The update may be a plurality of updates. The update may betransmitted to a client. The update may be transmitted to a financialinstitution. The update may be transmitted to a third party.

The update may be a first update. The first update may be transmitted toa first party. The first update may correspond to a first informationset. The first information set may include any suitable information. Theupdate may be a second update. The second update may be transmitted tothe first party. The second update may be transmitted to a second party.The second update may correspond to a second information set. The secondinformation set may include any suitable information.

The tool may transmit data. The data may be transmitted from the firstlocation to the second location. The data may be transmitted from afirst FPS to a second FPS. The first FPS may be located at the firstlocation. The second FPS may be located at the second location.

The transmitted data may correspond to an item. The transmitted data mayinclude tracking information.

The tool may receive an item. The item may be received at a secondlocation. The item may be a physical item. The item may be delivered.The delivery may be a delivery using a third party cash transferservice.

The tool may compare the data transmitted from the first location to thecharacteristics of the physical item received at the second location.The tool may determine if the transmitted data corresponds to the itemreceived.

The tool may determine if the total number of items received at thesecond location is equal to the total number of items transmitted fromthe first location. The tool may determine if the total monetary valueof items received at the second location is equal to the total value ofitems transmitted from the first location. The tool may determine if thedenominations of items received at the second location are equal to thedenominations of items transmitted from the first location.

The tool may identify one or more inconsistencies. The inconsistenciesmay be between data transmitted from the first location and itemsreceived at the second location.

The tool may retrieve electronic images. The images may be images of anitem. The image may be an image of the item captured at the firstlocation. The tool may compare the electronic image of the item to thephysical item. The physical item may be the item received at the secondlocation.

As will be appreciated by one of skill in the art, the inventiondescribed herein may be embodied in whole or in part as a method, a dataprocessing system, or a computer program product. Accordingly, theinvention may take the form of an entirely hardware embodiment, anentirely software embodiment or an embodiment combining software,hardware and any other suitable approach or apparatus.

Furthermore, such aspects may take the form of a computer programproduct stored by one or more computer-readable storage encoded mediahaving computer-readable program code, or instructions, embodied in oron the storage encoded media. Any suitable computer readable storageencoded media may be utilized, including hard disks, CD-ROMs, opticalstorage devices, magnetic storage devices, and/or any combinationthereof. In addition, various signals representing data or events asdescribed herein may be transferred between a source and a destinationin the form of electromagnetic waves traveling through signal-conductingencoded media such as metal wires, optical fibers, and/or wirelesstransmission encoded media (e.g., air and/or space).

Processes in accordance with the principles of the invention may includeone or more features of the processes illustrated in FIGS. 1 and 5-11.For the sake of illustration, the steps of the processes illustrated inFIGS. 1 and 5-11 will be described as being performed by a “system.” The“system” may include one or more of the features of the apparatus thatare shown or described herein and/or any other suitable device orapproach. The “system” may be provided by an entity. The entity may bean individual, an entity or any other suitable entity.

Illustrative information that is exchanged with the system may betransmitted and displayed using any suitable markup language under anysuitable protocol, such as those based on JAVA, COCOA, XML or any othersuitable and languages or protocols.

FIG. 1 shows a schematic diagram of exemplary system 100 for forecastingand validating data.

System 100 may include client 101. Client 101 may utilize system 100.Client 101 may utilize system 100 in communication with one or more offinancial institution 107, third-party 121 and third-party 123.

Client 101 may be any suitable entity, such as a retail, commercial orindustrial entity. Client 101 may be one of a plurality of clients.Client 101 may operate one or more client locations. For example, client101 may operate a first branch in a first location and a second branchin a second location. Client 101 may be any suitable client of afinancial institution. Client 101 may be located in a remote location.

Client 101 may be a client of a financial institution. The financialinstitution may operate one or both of institution 107. The financialinstitution may be any suitable financial institution, such as a branchor processing center.

Institution 107 may be operated by a third-party or any suitable vendoror contractor. Institution 107 may be a processing center. Institution107 may be a sorting center. Institution 107 may be operated by a cashdelivery or cash transfer service. Institution 107 may be operated by anarmored car provider.

System 100 may include Funds Processing System (“FPS”) 103. FPS 103 maybe the property of client 101. FPS 103 may be the property of financialinstitution. FPS 103 may be the property of institution 107. FPS 103 maybe placed at client 101 by the financial institution or by athird-party.

FPS 103 may be located in any suitable area within client 101. Forexample, FPS 103 may be located in a designated room, such as room 105.Alternatively, FPS 103 may be located in proximity to non-FPS items.

FPS 103 may receive one or more items. The item may be one or morefinancial instruments. The item may be one or more attachments.

FPS 103 may process the items. FPS 103 may generate data. The data maycorrespond to one or more items. The data may correspond to one or moreattributes of the items. FPS 103 may record or log one or attributes ofthe items. Exemplary attributes may include weight, dimensions, value,quantity, type or any other suitable attribute.

FPS 103 may store the items. The items may be stored until a pickup. Theitems may be stored within FPS 103. The items may be stored in acontainer adjacent or in proximity to FPS 103.

FPS 103 may store the data. The data may be stored in computer-readablememory. FPS 103 may transmit the data. The data may be transmittedimmediately upon creation of the data. For example, immediately afterthe weight of a bill is determined, the weight may be transmitted by theFPS. The weight may be stored by the FPS. The storage of the weight maybe for a transmission at a later time.

The data may be cross-referenced with one or more items. For example,data corresponding to a check may include a unique identifier. In afurther example, the physical check may be associated with a uniqueidentifier, to allow cross-referencing and retrieval.

FPS 103 may transmit the data over a communication network. Thecommunication may be any suitable communication network. Illustrativedata flow of the communication network may include flow 109. Flow 109shows the transmission of data from the FPS using the communicationnetwork. The data may continue the transmission via flow 111. Flow 111shows the arrival of the transmitted data. The transmitted data mayarrive at institution 107. The data may be transmitted directly from FPS103 to institution 107.

The data may be processed substantially entirely at FPS 103. FPS 103 mayprocess analytical models and forecasts associated with the data. Thedata may be processed at a point along the path of transmission. Forexample, the data may be transmitted by flow 109 to a server. The servermay process the data. The data may be processed by the financialinstitution.

The data may be used to generate forecast 113. Forecast 113 may begenerated at FPS 103. Forecast 113 may be generated by the financialinstitution. The data may be generated institution 107. Forecast 113 maybe generated at FPS 103 using institution software, hardware ornetworking. Forecast 113 may be generated at FPS 103 usingpre-configured programming. The pre-configured programming may beprogrammed by institution 107.

System 100 may include illustrative flows 117 and 119. Flow 117 is anillustrative flow of one or more items. Flow 117 may be the physicaltransfer of the items.

Flow 117 may be represented by vehicle 123. Vehicle 123 may be operatedby a financial institution. Vehicle 123 may be operated by a contractedthird-party. Vehicle 123 may transfer physical items from client 101.Vehicle 123 may pick up items at client 101. Vehicle 123 may transferthe items to institution 107. Institution 107 may be operated by afinancial institution. Institution 107 may be operated by a third-party.

Vehicle 123 may deliver the items to institution 107. The items may beprocessed at institution 107. Institution 107 may include a second FPS.Institution 107 may determine if the items are identical orsubstantially identical to the data received via flows 109 and 111. Atleast a portion of this determination may be accomplished using thesecond FPS. Institution 107 may determine inconsistencies or differencesbetween the data received via flows 109 and 111 and the items receivedvia vehicle 123.

Data corresponding to the inconsistencies may be analyzed. The datacorresponding to the inconsistencies may be stored in computer-readablememory for later review. The items associated with the inconsistenciesmay be analyzed. Characteristics of the physical items associated withthe data may be analyzed. Institution 107 may implement specified reviewprocedures for items associated with inconsistencies. Institution 107may store the items.

Vehicle 123 may transfer the items from institution 107 to institution125. Institution 125 may store the items. Institution 125 may processthe items. Institution 125 may include an FPS. Institution 125 maydetermine if the items are identical or substantially identical to thedata transmitted via flows 109 and 111. Institution 125 may determinethis using the FPS. Institution 125 may determine inconsistenciesbetween the data received via flows 109 and 111 and the items receivedvia vehicle 123.

Institution 125 may receive data. The data may be received via flow 127.The data may be received from Institution 107. The data may be identicalto the data transmitted from client 101 via flows 109 and 111. The datamay be different than the data transmitted from client 101 via flows 109and 111. For example, institution 125 may receive data corresponding tothe items. The data may include data not included in the datatransmitted via flows 109 and 111.

Flow 119 may be represented by vehicle 121. Vehicle 121 may besubstantially identical to vehicle 123. Vehicle may illustrate themovement of items. The movement may be the movement of financialinstruments. The financial instrument movement may be a delivery offinancial instruments to client 101.

FIG. 2 shows illustrative apparatus 200. Apparatus 200 may be a FundsProcessing System (“FPS”). FPS 200 may be a kiosk, terminal, standalonedevice, self-service terminal or any other suitable apparatus. FPS 200may be incorporated into system 100, discussed above. FPS 200 may be oneof a plurality of FPSs operating within system 100.

FPS 200 may be in communication with Electronic Communication Network N.The communication may be routed through Router R.

FPS 200 may include feeder 201. Feeder 201 may receive one or moreitems. Feeder 201 may include a mechanical gate. Feeder 201 may be anopening. Feeder 201 may include a conveyer belt.

Feeder 201 may be accessible by one or more individuals. Individual mayfeed or drop one or more items into feeder 201. Feeder 201 may transferthe items via a feeder network (not shown).

The feeder network may transfer the items to a sensor 231. Sensor 231may be any suitable sensor. Sensor 231 may be or include a scale,scanner, camera, bill counter, or sorter. Sensor 231 may determine oneor more attributes of an item received via feeder 201. Sensor 231 mayscan an item to determine an attribute.

Sensor 231 may transmit information to CPU 213. CPU 213 may instruct thefeeder network to transfer the item. CPU 213 may determine a destinationfor the item. The destination may be based on information received fromsensor 231. CPU 213 may instruct the feeder network to transfer the itemone or more of scanners 202, 203 and 204.

The feeder network may transfer the items to one or more of scanner 202,scanner 203 and scanner 204. Scanners 202, 203 and 204 may be locatedalong the feeder network. One or more of scanners 202, 203 and 204 mayreceive an item via the feeder network.

It should be noted that each of scanners 202, 203 and 204 may receivethe items via the feeder network directly from feeder 201.Alternatively, each of scanners 202, 203 and 204 may receive the itemsvia the feeder network from sensor 231.

Each of scanners 202, 203 and 204 may be designated to scan one or moreitems. Each scanner may be designated to scan one or more categories,types or denominations of items. For example, scanner 202 may bedesignated to scan checks. In a further example, scanners 202, 203 and204 may all be configured to scan all items.

Scanners 202, 203 and 204 may transmit information to CPU 213. Theinformation may be any suitable information. The information may bescans of one or more items. The scans may be processed to determinefurther attributes of the items. The scans may be processed by CPU 213.

CPU 213 may be associated, and in communication, with modem 211. Modem211 may communicate with Router R. CPU 213 may be associated with,and/or in communication with, one or more of memory 205 and transmitter207. CPU 213 may store data in memory 205. CPU 213 may transmit datausing transmitter 207 over electronic communication network N via modem211 and router R.

CPU 213 may instruct the feeder network to transfer one or more itemsfrom one or more of scanners 202, 203 and 204 to sorter 215. Sorter 215may be part of sensor 231. Sorter 215 may exist independent of sensor231. Sorter 215 may sort the items using any suitable sorting methods orsystems. Sorter 215 may sort the items based on data received from CPU213. The data may be data received from one or more of sensor 231 andscanners 202, 203 and 204.

The feeder network of FPS 200 may be complex and extensive. Thus, theflow and direction of items may be altered or customized. Therefore, allof the components within FPS 200 may be capable of communicating withone another. All of the components within FPS 200 may be capable oftransferring one or more items via the feeder network to one another.

For example, sorter 215 may transfer items directly to one or more ofstorage cartridges 217, 219 and 221. Storage cartridges 217, 219 and 221may be identical. Storage cartridges 217, 219 and 221 may be removablefrom FPS 200. Storage cartridges 217, 219 and 221 may each be configuredto store different items. The items may be differentiated using anysuitable method.

In another example, sorter 215 may transfer one or more items to one orboth of scale 227 and bill counter 229. Scale 227 may determine weightsof one or more items. Counter 229 may determine the quantity of one ormore items.

In a further example, scanners 202, 203 and 204 or sensor 231, maytransfer one or more items directly to storage cartridges 217, 219 and221.

FPS 200 may further include printer 209, barcode system 223 andcounterfeit determination system 225.

Printer 209 may be a part of barcode system 223. Printer 209 may printone or more barcodes. Printer 209 may print an identifier. Theidentifier may be stored in a storage cartridge. The identifier may bestored with one or more items. For example, printer 209 may print anidentifier. The identifier may correspond to a check. The identifier maybe stored in storage cartridge 217 with the check. This may allow forease of retrieval of data associated with the check.

Barcode system 223 may include a barcode generator, printer, and othersuitable components. Barcode system 223 may include a tracking system(not shown). Barcode system 223 may be a component of a tracking system.

Barcode system 223 may generate a unique barcode. The barcode may beprinted. The printed barcode may be affixed to one or more of storagecartridges 217, 219 and 221. The generating of a barcode may generate anassociated file. The file may be stored in memory 205.

Counterfeit determination system 225 may receive one or more items.Counterfeit determination system 225 may receive all items received viafeeder 201. Counterfeit determination system 225 may receive selecteditems. The items may be items selected for further review. The selectionmay be based upon an inadequate or indeterminable scan, a weight, or anyother suitable reason.

Counterfeit determination system 225 may include any suitablecounterfeit determination components, such as enhanced scanners,chemical analysis equipment, fiber analysis, or any other suitabledetermination mechanisms.

FIG. 3 may include system 300. System 300 may share one or more featureswith the apparatus shown in FIG. 2. System 300 illustrates a computingdevice 301 (alternatively referred to herein as a “server”) that may beused according to an illustrative embodiment of the invention. Thecomputer server 301 may have a processor 303 for controlling overalloperation of the server and its associated components, including RAM305, ROM 307, input/output (“I/O”) module 309, and memory 315.

I/O module 309 may include a microphone, keypad, touch screen and/orstylus through which a user of device 201 may provide input, and mayalso include one or more of a speaker for providing audio output and avideo display device for providing textual, audiovisual and/or graphicaloutput. Software may be stored within memory 315 and/or other storage(not shown) to provide instructions to processor 303 for enabling server301 to perform various functions. For example, memory 315 may storesoftware used by server 301, such as an operating system 317,application programs 319, and an associated database 311. Alternatively,some or all of server 301 computer executable instructions may beembodied in hardware or firmware (not shown).

Server 301 may operate in a networked environment supporting connectionsto one or more remote computers, such as terminals 341 and 351.Terminals 341 and 351 may be personal computers or servers that includemany or all of the elements described above relative to server 301. Thenetwork connections depicted in FIG. 3 include a local area network(LAN) 325 and a wide area network (WAN) 329, but may also include othernetworks. When used in a LAN networking environment, computer 301 isconnected to LAN 325 through a network interface or adapter 313. Whenused in a WAN networking environment, server 301 may include a modem 327or other means for establishing communications over WAN 329, such asInternet 331.

It will be appreciated that the network connections shown areillustrative and other means of establishing a communications linkbetween the computers may be used. The existence of any of variouswell-known protocols such as TCP/IP, Ethernet, FTP, HTTP and the like ispresumed, and the system can be operated in a client-serverconfiguration to permit a user to retrieve web pages from a web-basedserver. Any of various conventional web browsers can be used to displayand manipulate data on web pages.

Additionally, application program 319, which may be used by server 301,may include computer executable instructions for invoking userfunctionality related to communication, such as email, short messageservice (SMS), and voice input and speech recognition applications.

Computing device 301 and/or terminals 341 or 351 may also be mobileterminals including various other components, such as a battery,speaker, and antennas (not shown). Terminal 351 and/or terminal 341 maybe portable devices such as a laptop, tablet, smartphone or any othersuitable device for storing, transmitting and/or transporting relevantinformation.

Any information described above in connection with database 311, and anyother suitable information, may be stored in memory 315. One or more ofapplications 319 may include one or more algorithms that may be used toanalyze deposit reporting, analyze reconciliation of deposit reporting,process deposits, reconcile deposit reporting, and/or any other suitabletasks.

FIG. 4 shows an illustrative apparatus that may be configured inaccordance with the principles of the invention.

FIG. 4 shows illustrative apparatus 400. Apparatus 400 may share one ormore features with a computing machine. Apparatus 400 may be included inapparatus shown in FIG. 3 and/or FIG. 2. Apparatus 400 may include chipmodule 402, which may include one or more integrated circuits, and whichmay include logic configured to perform any other suitable logicaloperations.

Apparatus 400 may include one or more of the following components: I/Ocircuitry 404, which may include the transmitter device and the receiverdevice and may interface with fiber optic cable, coaxial cable,telephone lines, wireless devices, PHY layer hardware, a keypad/displaycontrol device or any other suitable encoded media or devices;peripheral devices 406, which may include counter timers, real-timetimers, power-on reset generators or any other suitable peripheraldevices; logical processing device 408, which may compute datastructural information, structural parameters of the data, quantifyindicies; and machine-readable memory 410.

Machine-readable memory 410 may be configured to store inmachine-readable data structures: data lineage information; datalineage, technical data elements; data elements; business elements;identifiers; associations; relationships; and any other suitableinformation or data structures.

Components 402, 404, 406, 408 and 410 may be coupled together by asystem bus or other interconnections 412 and may be present on one ormore circuit boards such as 420. In some embodiments, the components maybe integrated into a single silicon-based chip.

It will be appreciated that software components including programs anddata may, if desired, be implemented in ROM (read only memory) form,including CD-ROMs, EPROMs and EEPROMs, or may be stored in any othersuitable computer-readable medium such as but not limited to discs ofvarious kinds, cards of various kinds and RAMs. Components describedherein as software may, alternatively and/or additionally, beimplemented wholly or partly in hardware, if desired, using conventionaltechniques.

Various signals representing information described herein may betransferred between a source and a destination in the form ofelectromagnetic waves traveling through signal-conducting encoded mediasuch as metal wires, optical fibers, and/or wireless transmissionencoded media (e.g., air and/or space).

Apparatus 400 may operate in a networked environment supportingconnections to one or more remote computers via a local area network(LAN), a wide area network (WAN), or other suitable networks. When usedin a LAN networking environment, apparatus 400 may be connected to theLAN through a network interface or adapter in I/O circuitry 404. Whenused in a WAN networking environment, apparatus 400 may include a modemor other means (not shown) for establishing communications over the WAN.It will be appreciated that the network connections shown areillustrative and other means of establishing a communications linkbetween the computers may be used. The existence of any of variouswell-known protocols such as TCP/IP, Ethernet, FTP, HTTP and the like ispresumed, and the system may be operated in a client-serverconfiguration to permit a user to operate logical processing device 408,for example over the Internet.

Apparatus 400 may be included in numerous general purpose or specialpurpose computing system environments or configurations. Examples ofwell-known computing systems, environments, and/or configurations thatmay be suitable for use with the invention include, but are not limitedto, personal computers, server computers, hand-held or laptop devices,mobile phones and/or other personal digital assistants (“PDAs”),multiprocessor systems, microprocessor-based systems, tablets,programmable consumer electronics, network PCs, minicomputers, mainframecomputers, distributed computing environments that include any of theabove systems or devices, and the like.

FIG. 5 shows illustrative process 500. Process 500 may begin at step502.

At step 502, the system may establish an FPS. The FPS may be establishedby a client, financial institution or third party. The FPS may beestablished at a client location. The client location may be a remoteclient location. The client location may be remote from one or morefinancial institutions or processing centers.

At step 504, the system may receive a plurality of items. The items maybe received via the FPS established at step 502. The FPS may be at theclient location.

At step 506, the system may process the items received via the FPS. Theprocessing may include one or more aspects described in FIG. 2, asperformed by FPS 200.

At step 508, the system may transmit data. The data may be transmittedvia the FPS. The data may correspond to one or more items received atstep 504 and/or processed at step 506. The data may be transmitted to afinancial institution. The financial institution may be located at alocation remote from the client.

The system may continue to one of steps 514 and 516. At step 514, thesystem may forecast information. The forecasted information may bedetermined based on data. The data may be the data discussed in steps504-508. The data may be data received via the FPS. The data may includeexternal data. The external data may include any suitable data usefulfor forecasting information. The forecast may predict receipts. Thereceipts may be bank receipts. The bank receipts may correspond to oneor more of the items in steps 504-508.

At step 516, the system may forecast information. The forecastinformation may be determined based on data, such as the data receivedvia the FPS. The data may be external data. The forecast may predict oneor more deficiencies. The deficiency may be a client deficiency. Theclient deficiency may be a deficiency of cash on hand.

FIG. 6 shows illustrative process 600. Illustrative process 600 maybegin at step 602. Process 600 may be performed using any suitableapparatus, such as FPS 200 in FIG. 2.

At step 602, the system may sort one or more items. The items may besorted by type. The type may be a type of document, attachment, bill,denomination, value or any other suitable type differentiation.

At step 604, the system may compile an image. The image may be anelectronic image. The image may be an electronic image of each item. Theelectronic image may be compiled based on one or more methodsimplemented by one or more components of FPS 200 of FIG. 2.

At step 606, the system may compute a total. The total may be the totalnumber of items. The total may be the total number of items received viathe FPS. The total may be computed for any suitable time period, such asa daily total or monthly total.

At step 608, the system may calculate a value. The value may be amonetary value. The monetary value may be a total monetary value. Thetotal monetary value may be a total monetary value of the items receivedvia the FPS. The total may be calculated for any suitable time period,such as a weekly total or hourly total.

At step 610, the system may determine a quantity. The quantity may bethe quantity of items. The quantity of items may be a quantity of itemsfor each denomination. The quantity may be determined for any suitabletime period.

At step 612, the system may sort the items. The items may be sorted bydenomination.

At step 614, the system may transmit the electronic image from step 604.The electronic image may be an image of each item. The electronic imagemay be transmitted to a financial institution.

FIG. 7 shows illustrative process 700. Process may begin at step 702.

At step 702, the system may establish an FPS. The FPS may be establishedat a client location.

At step 704, the system may receive one or more items. The one or moreitems may be received via the FPS. The one or more items may be receivedat the client location.

At step 706, the system may process the items. The items may beprocessed via the FPS.

At step 708, the system may transmit data. The data may be datacorresponding to an item. The data may be transmitted to a financialinstitution. The data may be transmitted via the FPS.

At step 710, the system may forecast future requirements. The futurerequirements may be future delivery requirements. The deliveryrequirements may be financial instrument delivery requirements. Theforecast may be determined at the financial institution location. Theforecast may be determined at the client location. The forecast may bedetermined by the financial institution using the FPS at the clientlocation.

The forecast may be an aggregate forecast. The aggregate forecast may bea forecast for one or more client locations. The forecast may be aforecasted result and/or need at one or more client locations. Forexample, the forecast may be a forecast for future delivery requirementsfor multiple client locations of a client.

The multiple locations may be all client locations. The multiplelocations may be a subset of client locations. For example, futuredelivery requirements may be forecasted for client locations in ageographical region. The region may be defined by the client. Forexample, the region may the “northern region,” “region 4” or any othersuitable region. Alternatively, the forecasted region may be specifiedbased on well-known regional identifiers, such as state, county,municipality, time zone, or any other suitable identifier.

In another example, the future delivery requirements forecast may be aforecasted aggregate amount. The aggregate forecast may thereforepredict expected client requirements for cash on hand for a specifiedregion. For example, a forecast may predict a client need of $500,000 ofcash on hand, on a weekly basis, for “region 7.” In yet a furtherexample, the forecast may determine the aggregate requirements, as wellas the individual requirements, for each client location. Thus, theforecast may determine that a branch in a region, such as “Branch 3” in“region 8,” may require $150,000 of a $900,000 aggregated forecast.

At step 712, the system may forecast future requirements. The futurerequirements may be future pickup requirements. The pickup requirementsmay be item pickup requirements. The forecast may be determined at thefinancial institution location. The forecast may be determined theclient location. The forecast may be determined by the financialinstitution using the FPS at the client location.

FIG. 8 shows illustrative process 800. Process 800 may begin at step802.

At step 802, the system may analyze a trend. The trend may be a usagetrend. The trend may be a previous usage trend. The usage trend may be aclient usage trend. The usage trend may be a client usage trend of cashon hand.

At step 804, the system may evaluate current usage. The current usagemay be current client usage. The current usage may be client usage forthe current day. The current usage may be client current usage of cashon hand.

At step 806, the system may predict future deficiencies. The futuredeficiencies may be future client deficiencies. The future clientdeficiencies may be future deficiencies for cash on hand. Thedeficiencies may be predicted based on, at least in part, steps 802 and804.

FIG. 9 shows illustrative process 900. Process 900 may begin at step902.

At step 902, the system may analyze a trend. The trend may be a usagetrend. The usage trend may be a previous usage trend. The usage trendmay be a client usage trend. The client usage trend may be a trend ofclient usage of cash on hand.

At step 904, the system may evaluate current usage. The current usagemay be current client usage. The current usage may be client usage forthe current day. The current usage may be client current usage of cashon hand.

At step 906, the system may predict future deficiencies. The futuredeficiencies may be future client deficiencies. The future clientdeficiencies may be future deficiencies for cash on hand. Thedeficiencies may be predicted based on, at least in part, steps 902 and904.

At step 908, the system may transmit a recommendation. Therecommendation may be a recommendation to modify a schedule. Theschedule may be a delivery schedule.

Steps 910, 912 and 914 include one or more available modificationoptions.

At step 910, the system may modify a schedule. The schedule may bemodified based on a request. The request may be a request for animmediate transfer. The immediate transfer may be an immediate transferof one or more financial instruments.

At step 912, the system may modify a schedule. The schedule may bemodified based on a request. The request may be a request to modify thedelivery schedule for the remainder of a current day.

At step 914, the system may modify a schedule. The schedule may bemodified based on a request. The request may be a request to modify afuture delivery schedule.

At step 916, the system may modify all future delivery schedules.

At step 918, the system may modify the future delivery for the followingday.

FIG. 10 shows illustrative process 1000. Process 1000 may begin at step1002.

At step 1002, the system may analyze a trend. The trend may be a usagetrend. The usage trend may be a previous usage trend. The usage trendmay be a client usage trend. The client usage trend may be a trend ofclient usage of cash on hand. The usage trend may be a client usagetrend of cash on hand for each denomination.

At step 1004, the system may evaluate current usage. The current usagemay be current client usage. The current usage may be client usage forthe current day. The current usage may be client current usage of cashon hand. The current usage may be current client usage of cash on handfor each denomination.

At step 1006, the system may calculate a difference. The difference maybe a statistical difference. The statistical difference may be adifference between previous usage trends and current rate of usage.

At step 1008, the system may predict future deficiencies. The futuredeficiencies may be future client deficiencies. The future clientdeficiencies may be future deficiencies for cash on hand. The futureclient deficiencies for cash on hand may be future deficiencies of cashon hand for each denomination. The deficiencies may be predicted basedon, at least in part, steps 1002, 1004 and 1006.

At step 1010, the system may transmit a recommendation. Therecommendation may be transmitted to a financial institution. Therecommendation may be a recommended schedule. The schedule may be arecommended replenishment schedule. The replenishment may be financialinstrument replenishment. The replenishment may be a replenishment foreach financial instrument denomination.

FIG. 11 shows illustrative process 1100. Process 1100 may begin at step1102.

At step 1102, the system may analyze a trend. The trend may be a usagetrend. The usage trend may be a previous usage trend. The usage trendmay be a client usage trend. The client usage trend may be a trend ofclient usage of cash on hand. The usage trend may be a client usagetrend of cash on hand for each denomination.

At step 1104, the system may predict a deficiency. The deficiency may bea future deficiency. The deficiency may be a client deficiency. Thedeficiency may be a future client deficiency for cash on hand.

At step 1106, the system may calculate a time. The time may be apreferred or optimal time. The time may be a preferred time for adelivery. The delivery may be a cash delivery. The delivery may be acash replenishment delivery.

The invention may be operational with numerous other general purpose orspecial purpose computing system environments or configurations.Examples of well-known computing systems, environments, and/orconfigurations that may be suitable for use with the invention include,but are not limited to, personal computers, server computers, hand-heldor laptop devices, tablets, mobile phones and/or other personal digitalassistants (“PDAs”), multiprocessor systems, microprocessor-basedsystems, programmable consumer electronics, network PCs, minicomputers,mainframe computers, distributed computing environments that include anyof the above systems or devices, and the like.

The invention may be described in the general context ofcomputer-executable instructions, such as program modules, beingexecuted by a computer. Generally, program modules include routines,programs, objects, components, data structures, etc. that performparticular tasks or implement particular abstract data types. Theinvention may also be practiced in distributed computing environmentswhere tasks are performed by remote processing devices that are linkedthrough a communications network. In a distributed computingenvironment, program modules may be located in both local and remotecomputer storage encoded media including memory storage device.

One of ordinary skill in the art will appreciate that the elements shownand described herein may be performed in other than the recited orderand that one or more elements illustrated may be optional. The methodsof the above-referenced embodiments may involve the use of any suitableelements, elements, computer-executable instructions, orcomputer-readable data structures. In this regard, other embodiments aredisclosed herein as well that can be partially or wholly implemented ona computer-readable medium, for example, by storing computer-executableinstructions or modules or by utilizing computer-readable datastructures.

Thus, systems or methods for deposit information reporting andreconciliation of information reporting are therefore provided. Personsskilled in the art will appreciate that the present invention can bepracticed by other than the described embodiments, which are presentedfor purposes of illustration rather than of limitation, and that thepresent invention is limited only by the claims that follow.

What is claimed is:
 1. An apparatus for tracking items, the apparatuscomprising: a funds processing device (“FPD”), wherein the FPD isestablished at a client location; a receiver including hardwareconfigured to receive, via the FPD, a plurality of items, said itemscomprising: one or more financial instruments; and one or moreattachments; a processor configured to process, via the FPD, theplurality of items; and a transmitter configured to transmit, via theFPD, to a financial institution, data corresponding to the items,wherein, the processor is further configured to calculate an estimatedarrival time of the items at the financial institution and the receiveris further configured to receive tracking information; a barcode deviceresiding within the FPD, said barcode device comprising: a barcodegenerator configured to generate a unique barcode; a barcode printerconfigured to print the unique barcode; and an affixer device configuredto affix the barcode to a container storing at least a portion of theitems, wherein the barcode is configured to provide, at a secondlocation, the tracking information for confirming the estimated arrivaltime of the container.
 2. The apparatus of claim 1 further comprising:the receiver further configured to receive data corresponding to ascanning of the barcode; and the processor further configured to:produce updated tracking information based at least in part on the data;and recalculate, based on the updated tracking information, theestimated arrival time of the items at the financial institution.
 3. Theapparatus of claim 2 wherein the estimated arrival time is calculatedbased on an analysis of previous cash transfer data.
 4. The apparatus ofclaim 3 wherein the previous cash transfer data comprises datacorresponding to financial institution processing volume.
 5. Theapparatus of claim 3 wherein the previous cash transfer data comprisesdata corresponding to average time to process a pre-determined number ofitems.
 6. The apparatus of claim 3 wherein the previous cash transferdata comprises data corresponding to time of transit.
 7. The apparatusof claim 1 further comprising: the receiver further configured toreceive current condition data; and the processor further configured tocalculate the estimated arrival time based on the current conditiondata.
 8. The apparatus of claim 7 wherein current condition datacomprises: current traffic conditions; current weather conditions;current processing center volume; time of day; current location of theitems; number of non-cash items; number of cash items; and number offlagged items.
 9. The apparatus of claim 1 further comprising theprocessor further configured to forecast an estimated time of cash flowavailability.